» Articles » PMID: 36599983

Integrated Intracellular Organization and Its Variations in Human IPS Cells

Overview
Journal Nature
Specialty Science
Date 2023 Jan 4
PMID 36599983
Authors
Affiliations
Soon will be listed here.
Abstract

Understanding how a subset of expressed genes dictates cellular phenotype is a considerable challenge owing to the large numbers of molecules involved, their combinatorics and the plethora of cellular behaviours that they determine. Here we reduced this complexity by focusing on cellular organization-a key readout and driver of cell behaviour-at the level of major cellular structures that represent distinct organelles and functional machines, and generated the WTC-11 hiPSC Single-Cell Image Dataset v1, which contains more than 200,000 live cells in 3D, spanning 25 key cellular structures. The scale and quality of this dataset permitted the creation of a generalizable analysis framework to convert raw image data of cells and their structures into dimensionally reduced, quantitative measurements that can be interpreted by humans, and to facilitate data exploration. This framework embraces the vast cell-to-cell variability that is observed within a normal population, facilitates the integration of cell-by-cell structural data and allows quantitative analyses of distinct, separable aspects of organization within and across different cell populations. We found that the integrated intracellular organization of interphase cells was robust to the wide range of variation in cell shape in the population; that the average locations of some structures became polarized in cells at the edges of colonies while maintaining the 'wiring' of their interactions with other structures; and that, by contrast, changes in the location of structures during early mitotic reorganization were accompanied by changes in their wiring.

Citing Articles

Deep-learning-based image compression for microscopy images: An empirical study.

Zhou Y, Sollmann J, Chen J Biol Imaging. 2025; 4():e16.

PMID: 39776609 PMC: 11704128. DOI: 10.1017/S2633903X24000151.


Quantitative determination of the spatial distribution of components in single cells with CellDetail.

Schuster T, Amoah A, Vollmer A, Marka G, Niemann J, Sacma M Nat Commun. 2024; 15(1):10250.

PMID: 39592623 PMC: 11599593. DOI: 10.1038/s41467-024-54638-8.


Organelle landscape analysis using a multiparametric particle-based method.

Kurikawa Y, Koyama-Honda I, Tamura N, Koike S, Mizushima N PLoS Biol. 2024; 22(9):e3002777.

PMID: 39288101 PMC: 11407678. DOI: 10.1371/journal.pbio.3002777.


Mantis: High-throughput 4D imaging and analysis of the molecular and physical architecture of cells.

Ivanov I, Hirata-Miyasaki E, Chandler T, Cheloor-Kovilakam R, Liu Z, Pradeep S PNAS Nexus. 2024; 3(9):pgae323.

PMID: 39282007 PMC: 11393572. DOI: 10.1093/pnasnexus/pgae323.


Interpretable representation learning for 3D multi-piece intracellular structures using point clouds.

Vasan R, Ferrante A, Borensztejn A, Frick C, Gaudreault N, Mogre S bioRxiv. 2024; .

PMID: 39091871 PMC: 11291148. DOI: 10.1101/2024.07.25.605164.


References
1.
Kirschner M, Gerhart J, Mitchison T . Molecular "vitalism". Cell. 2000; 100(1):79-88. DOI: 10.1016/s0092-8674(00)81685-2. View

2.
Woese C . A new biology for a new century. Microbiol Mol Biol Rev. 2004; 68(2):173-86. PMC: 419918. DOI: 10.1128/MMBR.68.2.173-186.2004. View

3.
Karsenti E . Self-organization in cell biology: a brief history. Nat Rev Mol Cell Biol. 2008; 9(3):255-62. DOI: 10.1038/nrm2357. View

4.
Rafelski S, Marshall W . Building the cell: design principles of cellular architecture. Nat Rev Mol Cell Biol. 2008; 9(8):593-602. DOI: 10.1038/nrm2460. View

5.
Roggiani M, Goulian M . Oxygen-Dependent Cell-to-Cell Variability in the Output of the Escherichia coli Tor Phosphorelay. J Bacteriol. 2015; 197(12):1976-87. PMC: 4438215. DOI: 10.1128/JB.00074-15. View